Exploiting smart city technology

A large family of viruses known as coronaviruses can cause various illnesses, ranging from the common cold to more severe diseases like severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In 2020, the World Health Organization (WHO) declared the newly identified coronavirus disease 2019 (COVID-19) a global pandemic after its initial outbreak in China in 2019. As 2019 ended, humanity was blindsided by an unexpected foe: the highly contagious respiratory illness COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This global pandemic presented unprecedented challenges, particularly in densely populated urban areas. Yet, amidst these struggles, smart cities emerged as beacons of innovation, harnessing technology to prioritize public health and safety in a rapidly urbanizing world. This work investigates the crucial role of AI-powered COVID-19 detection and classification systems in smart city environments. These systems leverage data analytics and artificial intelligence to effectively monitor and manage the virus’s spread. The study assesses the performance of two distinct datasets using various evaluation metrics. Notably, Mobile Net V2 and very deep convolution network (VGG19) models achieved remarkable accuracy, exceeding 97% for binary classifications (COVID-19/normal, COVID-19/pneumonia) and exceeding 92% for a three-class model (COVID-19/pneumonia/normal). Beyond accuracy, the work delves deep into the intricate components of these innovative solutions, encompassing advanced image processing techniques, machine learning algorithms, and real-time data analysis capabilities. In essence, this work paves the way for smart cities to leverage AI as a potent weapon in the fight against COVID-19, ultimately safeguarding public health and well-being. Harnessing technology for healthier cities, early detection and analysis powered by smart city systems can significantly bolster urban resilience against infectious diseases like COVID-19. This not only reduces pressure on healthcare infrastructure but also minimizes economic disruptions caused by lockdowns. Moreover, valuable data gleaned from these systems can guide long-term urban planning and public health initiatives, safeguarding resident well-being.